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2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541)
Independent component analysis is often approached from an information theoretic perspective employing specific sample estimates for the mutual information between the separated outputs. These approximations involve the nonparametric estimation of signal entropies. The common approach involves the estimation of these quantities and adaptation based on these criteria. In contrast, in this paper, we propose a Gaussianization-based approach, where the separation is performed in two stages:doi:10.1109/ijcnn.2004.1379868 fatcat:db7dfzahkbe65c3kt5vcrndmwu